Survey of Marketing Agents, Agent-Based Models, and Generative AI in Marketing

Generative AI and Agent-Based Models (ABMs) are transforming marketing with the ability to develop accurate, adaptive, and consumer-centered strategies. ABMs model interactions among agents such as consumers, firms, and influencers to reveal behavioral patterns and campaign optimization. At the same time, Large Language Models (LLMs) are elevating content creation, customer experience, and campaign management. This survey addresses where these technologies overlap to power contemporary marketing innovations, resolving for privacy, scalability, and ethics. Drawing on empirical case studies and current advances in multimodal and reinforcement learning, the book targets hybrid frameworks as well as future paths in ethical AI, green algorithms, and additional personalization.

Authors

Institutions

Publication Details

Published
2025-05-09
DOI
https://doi.org/10.1109/ginotech63460.2025.11076643
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Survey of Marketing Agents, Agent-Based Models, and Generative AI in Marketing

Sai Kumar Arava, Harsha Vardhan Puvvadi, Meghana Puvvadi, Adarsh Santoria et al.
Opinion Dynamics and Social Influence
article

Survey of Marketing Agents, Agent-Based Models, and Generative AI in Marketing

Sai Kumar Arava, Harsha Vardhan Puvvadi, Meghana Puvvadi, Adarsh Santoria, Sesha Sai Prasanna Chennupati
article en

Abstract

Generative AI and Agent-Based Models (ABMs) are transforming marketing with the ability to develop accurate, adaptive, and consumer-centered strategies. ABMs model interactions among agents such as consumers, firms, and influencers to reveal behavioral patterns and campaign optimization. At the same time, Large Language Models (LLMs) are elevating content creation, customer experience, and campaign management. This survey addresses where these technologies overlap to power contemporary marketing innovations, resolving for privacy, scalability, and ethics. Drawing on empirical case studies and current advances in multimodal and reinforcement learning, the book targets hybrid frameworks as well as future paths in ethical AI, green algorithms, and additional personalization.

Adobe Systems (United States) (US), Shell (India) (IN), Rippe Health (US), Indian Institute of Technology Mandi (IN)
Openalex Percentile: Top 84%
Opinion Dynamics and Social Influence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Survey of Marketing Agents, Agent-Based Models, and Generative AI in Marketing — Sai Kumar Arava, Harsha Vardhan Puvvadi, et al. · (2025) | TGRS Research Map | TGRS